The present invention relates to social bookmarking, and more specifically, to techniques for personalized tag recommendation for enterprise social bookmarking systems.
Social bookmarking has gained popularity among internet users. In most social bookmarking systems, users may annotate their bookmarked resources using text terms, which are usually referred to as tags. There are two major purposes for such tagging activities. First, tagging helps users to categorize their bookmarks and facilitate future retrieval of resources in different categories. Second, by making tags on one's bookmarks viewable by other users, tagging allows users to share useful resources they found with others, which is beneficial to the entire community.
Social bookmarking systems allow users to choose the terms they like to tag resources. Many social bookmarking systems also suggest tags to users based on the target resources. Tag recommendation can bring in a number of benefits. For example, tag recommendation makes tagging an easier task and thus encourages users to tag more often. By successfully predicting the tags a user would like to apply on a resource, tag recommendation may save users time on typing. Also, the suggested tags may remind users on the content of the corresponding resources so as to help them better annotate the resources. In addition, Tag recommendation may improve the quality of tags. By allowing users to click on a suggested tag instead of typing, tag recommendation may reduce the usage of simplified or incomplete terms in tags and reduce the occurrences of typos. Tag recommendation may also encourage the consistency of term selection in one's tags.